In this paper, we develop a numerically efficient scheme for set-membership prediction and filtering for discrete-time nonlinear systems, that takes into explicit account the effects of nonlinearities via local second-order information. The filtering scheme is based on a classical prediction/update recursion that requires at each step the solution of a convex semidefinite optimization problem. The technical results discussed in the paper build upon the recently developed paradigm of uncertain linear equations (ULE) and semidefinite relaxations.
Set-Membership Nonlinear Filtering with Second-Order Information / Calafiore, Giuseppe Carlo; Bona, Basilio. - (2005). (Intervento presentato al convegno IFAC05 World Congress tenutosi a Prague nel 4-8 July 2005) [10.3182/20050703-6-CZ-1902.00206].
Set-Membership Nonlinear Filtering with Second-Order Information
CALAFIORE, Giuseppe Carlo;BONA, Basilio
2005
Abstract
In this paper, we develop a numerically efficient scheme for set-membership prediction and filtering for discrete-time nonlinear systems, that takes into explicit account the effects of nonlinearities via local second-order information. The filtering scheme is based on a classical prediction/update recursion that requires at each step the solution of a convex semidefinite optimization problem. The technical results discussed in the paper build upon the recently developed paradigm of uncertain linear equations (ULE) and semidefinite relaxations.Pubblicazioni consigliate
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https://hdl.handle.net/11583/1408003
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